Improving the Performance of SSVEP BCI with Short Response Time by Temporal Alignments Enhanced CCA

Aung Aung Phyo Wai, Min Ho Lee, Seong Whan Lee, Cuntai Guan

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Steady State Visual Evoked Potentials (SSVEP) based Brain Computer Interface (BCI) provides high throughput in communication. In SSVEP-BCI, typically, higher accuracy can be achieved with a relatively longer response time. It is therefore a research topic to reduce the response time while keeping high accuracy. We propose a new method, temporal alignments enhanced Canonical Correlation Analysis (TACCA), followed by a decision fusion to improve classification accuracy with short response time. TACCA exploits linear correlation with non-linear similarity between steady-state responses and stimulus frequencies. We compare TACCA and three state-of-the-art methods using data from 54-subjects with response time ranging from 0.5 to 4 seconds. The evaluation results show that TACCA yields mean significant accuracy increase of 10-30% in all segment lengths, especially for the shorter time segment. One-way ANOVA tests show high significant differences between single and multiple phases in TACCA performance.

Original languageEnglish
Title of host publication9th International IEEE EMBS Conference on Neural Engineering, NER 2019
PublisherIEEE Computer Society
Pages155-158
Number of pages4
ISBN (Electronic)9781538679210
DOIs
Publication statusPublished - 2019 May 16
Externally publishedYes
Event9th International IEEE EMBS Conference on Neural Engineering, NER 2019 - San Francisco, United States
Duration: 2019 Mar 202019 Mar 23

Publication series

NameInternational IEEE/EMBS Conference on Neural Engineering, NER
Volume2019-March
ISSN (Print)1948-3546
ISSN (Electronic)1948-3554

Conference

Conference9th International IEEE EMBS Conference on Neural Engineering, NER 2019
CountryUnited States
CitySan Francisco
Period19/3/2019/3/23

Fingerprint

Brain computer interface
Bioelectric potentials
Analysis of variance (ANOVA)
Fusion reactions
Throughput
Communication

ASJC Scopus subject areas

  • Artificial Intelligence
  • Mechanical Engineering

Cite this

Phyo Wai, A. A., Lee, M. H., Lee, S. W., & Guan, C. (2019). Improving the Performance of SSVEP BCI with Short Response Time by Temporal Alignments Enhanced CCA. In 9th International IEEE EMBS Conference on Neural Engineering, NER 2019 (pp. 155-158). [8716985] (International IEEE/EMBS Conference on Neural Engineering, NER; Vol. 2019-March). IEEE Computer Society. https://doi.org/10.1109/NER.2019.8716985

Improving the Performance of SSVEP BCI with Short Response Time by Temporal Alignments Enhanced CCA. / Phyo Wai, Aung Aung; Lee, Min Ho; Lee, Seong Whan; Guan, Cuntai.

9th International IEEE EMBS Conference on Neural Engineering, NER 2019. IEEE Computer Society, 2019. p. 155-158 8716985 (International IEEE/EMBS Conference on Neural Engineering, NER; Vol. 2019-March).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Phyo Wai, AA, Lee, MH, Lee, SW & Guan, C 2019, Improving the Performance of SSVEP BCI with Short Response Time by Temporal Alignments Enhanced CCA. in 9th International IEEE EMBS Conference on Neural Engineering, NER 2019., 8716985, International IEEE/EMBS Conference on Neural Engineering, NER, vol. 2019-March, IEEE Computer Society, pp. 155-158, 9th International IEEE EMBS Conference on Neural Engineering, NER 2019, San Francisco, United States, 19/3/20. https://doi.org/10.1109/NER.2019.8716985
Phyo Wai AA, Lee MH, Lee SW, Guan C. Improving the Performance of SSVEP BCI with Short Response Time by Temporal Alignments Enhanced CCA. In 9th International IEEE EMBS Conference on Neural Engineering, NER 2019. IEEE Computer Society. 2019. p. 155-158. 8716985. (International IEEE/EMBS Conference on Neural Engineering, NER). https://doi.org/10.1109/NER.2019.8716985
Phyo Wai, Aung Aung ; Lee, Min Ho ; Lee, Seong Whan ; Guan, Cuntai. / Improving the Performance of SSVEP BCI with Short Response Time by Temporal Alignments Enhanced CCA. 9th International IEEE EMBS Conference on Neural Engineering, NER 2019. IEEE Computer Society, 2019. pp. 155-158 (International IEEE/EMBS Conference on Neural Engineering, NER).
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